Apparatus and method for verifying repeatability of spectroscope, and apparatus for analyzing spectrum data

ABSTRACT

A method of verifying repeatability of a spectroscope that irradiates light to a user sample, detects light reflected from the user sample, and measures spectrum data of the user sample, includes: verifying repeatability of the spectrum data, measured by the spectroscope, based on repeatability verification criteria; and controlling the spectroscope whether or not to remeasure the spectrum data, based on the verifying.

CROSS-REFERENCE TO RELATED APPLICATIONS

This is a Divisional of U.S. application Ser. No. 15/215,050 filed Jul.20, 2016, which claims priority from Korean Patent Application No.10-2015-0108288, filed Jul. 30, 2015, in the Korean IntellectualProperty Office. The disclosure of above-named applications areincorporated by reference herein in their entireties.

BACKGROUND 1. Field

The following description relates to an apparatus and method forverifying repeatability of a spectroscope, and an apparatus foranalyzing spectrum data, which applies the apparatus and method.

2. Description of the Related Art

A spectroscope is an instrument used to examine properties of light fora specific portion of the electromagnetic spectrum and typically used inspectroscopic analysis to identify materials. A measurement variable isgenerally the light's intensity, but could also be the polarization.

Due to the recent development of mobile devices, such as smartphones,tablet PCs, etc., health-care devices with a spectroscope combined witha mobile device are being developed. These health-care devices areminimized to be attached to or operate in association with smartphonesor tablet PCs. In addition, these health-care devices can diagnose andmanage a personal health condition and analyze all types of diseasesquantitatively.

Meanwhile, due to the minimization of mobile devices, the size of thespectroscope being installed becomes smaller, and this may lead todifficulties in a precise diagnosis and analysis due to a spectroscope'sperformance degradation and an increase in noise that is caused byexternal environmental factor.

SUMMARY

Exemplary embodiments address at least the above problems and/ordisadvantages and other disadvantages not described above. Also, theexemplary embodiments are not required to overcome the disadvantagesdescribed above, and may not overcome any of the problems describedabove.

According to an aspect of an exemplary embodiment, an apparatus forverifying repeatability of a spectroscope that irradiates light to auser sample, detects light reflected from the user sample, and measuresspectrum data of the user sample includes: a verifier to verifyrepeatability of spectrum data, measured by the spectroscope, based onpredefined repeatability verification criteria; and a controller tocontrol the spectroscope whether to remeasure the spectrum data based onthe verification result.

The predefined repeatability verification criteria may include asimilarity verification, a difference verification, a statisticalverification, and a combination of two or more thereof.

In response to the similarity verification among the predefinedrepeatability verification criteria, the verifier may calculate a degreeof similarity between a plurality of spectrum data, measured by thespectroscope, by using at least one of Pearson correlation, Kendallcorrelation, and Spearman correlation.

In response to the difference verification among the predefinedrepeatability verification criteria, the verifier may calculate a degreeof difference between a plurality of spectrum data, measured by thespectroscope, by using at least one of Euclidean distance, Manhattandistance, and Hamming distance, and verify the repeatability thereofbased on the calculated degree of difference.

In response to the statistical verification among the predefinedrepeatability verification criteria, the verifier may calculatestatistical data of a plurality of spectrum data, measured by thespectroscope, by using statistical techniques that include at least oneof a paired T-test and a paired Z-test, and verify the repeatabilitythereof based on the calculated statistical data.

The verifier may verify repeatability of currently measured spectrumdata based on the predefined repeatability verification criteria byusing at least one of values of mean and median of the spectrum datathat is previously measured by the spectroscope.

The controller may in response to the spectrum data having failed topass the repeatability verification, control the spectroscope toremeasure the spectrum data; and in response to the spectrum data havingpassed the repeatability verification, control an apparatus foranalyzing spectrum data to analyze the measured spectrum data.

The controller may control the spectroscope by determining a number ofremeasurement times, or control the apparatus for analyzing spectrumdata by determining spectrum data to be analyzed, based on at least oneof a number of spectrum data having passed the repeatabilityverification, a rate thereof, and a number of times that each spectrumdata has failed to pass the repeatability verification.

According to an aspect of an exemplary embodiment, an apparatus foranalyzing spectrum data includes: a spectroscopy unit, which includes alight source that irradiates light to a user sample, a detector thatdetects light reflected from the user sample, and a spectrum acquirerthat acquires spectrum data from the detected light; a verifier toverify repeatability of the acquired spectrum data based on predefinedrepeatability verification criteria; and a calculator to generate usersample analysis information by analyzing at least a part of the acquiredspectrum data based on the verification result.

The predefined repeatability verification criteria may include asimilarity verification, a difference verification, a statisticalverification, and a combination of two or more thereof.

The verifier may, based on the verification result, control thespectroscopy unit to remeasure the spectrum data, or control thecalculator to analyze at least a part of a plurality of spectrum dataacquired by the spectroscopy unit.

The verifier may control the calculator by determining spectrum data tobe analyzed, based on at least one of a number of spectrum data havingpassed the repeatability verification, a rate thereof, and a number oftimes that each spectrum data has failed to pass the repeatabilityverification.

The verifier may calculate at least one of values of mean, median, max,and min of the spectrum data that is determined to be analyzed, andprovide the calculation result to the calculator.

The apparatus may further include an information provider configured toprovide the generated user sample analysis information to a user.

According to an aspect of an exemplary embodiment, a method of verifyingrepeatability of a spectroscope that irradiates light to a user sample,detects light reflected from the user sample, and measures spectrum dataof the user sample includes: verifying repeatability of spectrum data,measured by the spectroscope, based on predefined repeatabilityverification criteria; and controlling, based on the verificationresult, the spectroscope whether to remeasure the spectrum data.

The predefined repeatability verification criteria may include asimilarity verification, a difference verification, a statisticalverification, and a combination of two or more thereof.

The verifying of the repeatability of spectrum data may includeverifying repeatability of currently measured spectrum data based on thepredefined repeatability verification criteria by using at least one ofvalues of mean and median of the spectrum data that is previouslymeasured by the spectroscope.

The controlling of the spectroscope may include: in response to thespectrum data having failed to pass the repeatability verification,controlling the spectroscope to remeasure the spectrum data; and inresponse to the spectrum data having passed the repeatabilityverification, controlling an apparatus for analyzing spectrum data toanalyze the measured spectrum data.

The controlling of the spectroscope may include controlling thespectroscope by determining a number of remeasurement times, orcontrolling the apparatus for analyzing spectrum data by determiningspectrum data to be analyzed, based on at least one of a number ofspectrum data having passed the repeatability verification, a ratethereof, and a number of times that each spectrum data has failed topass the repeatability verification.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and/or other aspects will become more apparent by describingcertain exemplary embodiments with reference to the accompanyingdrawings, in which:

FIG. 1 is a diagram illustrating an apparatus for verifyingrepeatability according to an exemplary embodiment.

FIGS. 2A and 2B are examples for the description of spectrum dataaccording to an exemplary embodiment.

FIG. 3 is a diagram illustrating a method of verifying the repeatabilityof spectrum data by a verifier according to an exemplary embodiment.

FIG. 4 is a diagram illustrating a controller according to an exemplaryembodiment.

FIG. 5 is a diagram illustrating an apparatus for analyzing spectrumdata according to an exemplary embodiment.

FIG. 6 is a diagram illustrating a spectroscopy unit according to anexemplary embodiment.

FIG. 7 is a flowchart illustrating a method of verifying repeatabilityaccording to an exemplary embodiment.

FIG. 8 is a detailed flowchart illustrating a method of verifyingrepeatability according to an exemplary embodiment.

FIG. 9 is a detailed flowchart illustrating an operation of controllingwhether to remeasure spectrum data according to an exemplary embodiment.

DETAILED DESCRIPTION

Certain exemplary embodiments are described in greater detail below withreference to the accompanying drawings.

In the following description, like drawing reference numerals are usedfor like elements, even in different drawings. The matters defined inthe description, such as detailed construction and elements, areprovided to assist in a comprehensive understanding of the exemplaryembodiments. However, it is apparent that the exemplary embodiments canbe practiced without those specifically defined matters. Also,well-known functions or constructions are not described in detail sincethey would obscure the description with unnecessary detail.

FIG. 1 is a diagram illustrating a verification apparatus 100 forverifying repeatability according to an exemplary embodiment.

Referring to FIG. 1, the verification apparatus 100 includes a verifier110, e.g., a processor or a microprocessor, and a controller 130, e.g.,a processor or a microprocessor.

The verification apparatus 100 may verify the repeatability of aspectroscope 10 that irradiates light to a user sample, detects thelight reflected from the user sample, and measures spectrum data of theuser sample.

In the case where the spectroscope 10 measures only one spectrum data,the spectroscope 10 fails to check measurement errors being generated inthe measured spectrum, or noises being added thereto. However, when aplurality of spectrum data is measured, the plurality of the measuredspectrum data is compared to each other, thereby checking the spectrumdata including the generated measurement errors or the added noises.

The verifier 110 may verify the repeatability of the spectrum data,measured by the spectroscope 10, based on predefined repeatabilityverification criteria.

The predefined repeatability verification criteria may include at leastone among a similarity verification, a difference verification, astatistical verification, or a combination of two or more of theverification criteria.

The predefined repeatability verification criteria may be, for example,the similarity verification. It may be assumed that the verifier 110receives the input of three spectrum data from the spectroscope 10. Theverifier 110 may calculate degrees of similarity between the threespectrum data. Here, the degree of similarity may be calculated byforming the three spectrum data in group of two in pair, which resultsin three degrees of similarity (3C2=3). Afterwards, in the case wherethe resultant three degrees of similarity are higher than a certaincriterion, the verifier 110 may determine that the three spectrum datahave passed the repeatability verification. Alternatively, in the casewhere the part of the three degrees of similarity is less than or equalto a certain criterion, the verifier 110 determines that the threespectrum data has failed to pass the repeatability verification.

In another example, the predefined repeatability verification criteriamay be the difference verification. As in the description aboveregarding the similarity verification, it is assumed that the verifier110 receive the input of three spectrum data from the spectroscope 10.Under that assumption, in the case where the resultant three degrees ofdifference are less than or equal to a certain criterion, the verifier110 may determine that the three spectrum data have passed therepeatability verification. Alternatively, in the case where the part ofthe three degrees of difference is higher than a certain criterion, theverifier 110 determines that three spectrum data have failed to pass therepeatability verification.

In yet another example, the predefined repeatability verificationcriteria may be the statistical verification. In this case as well as inthe description above, depending on whether the resultant threestatistical data are higher than a certain criterion, the verifier 110may determine that the three spectrum data have passed the repeatabilityverification, or that the three spectrum data have failed to pass therepeatability verification,.

In still yet another example, the verifier 110 may verify therepeatability of spectrum data based on predefined repeatabilityverification criteria, which include a similarity verification, adifference verification, a statistical verification, or the combinationof two or more of the verification criteria, on a basis of currentlymeasured spectrum data and the value, which is generated based on aplurality of spectrum data that is previously measured from thespectroscope 110.

The verifier 110 may, based on at least one of a specific duration and aspecific number of times, generate at least one of the values of mean,median, maximum (max), and minimum (min) by using the spectrum data thathas been received before the present measurement point in time. Forexample, the verifier 110 may generate at least one of the values ofmean and median by using spectrum data that has been measured within tenminutes from a present point in time or using spectrum data that hasbeen measured since the ten times before the present point in time.

In addition, the verifier 110 may verify the repeatability of thespectrum data by comparing the generated value and the currentlymeasured spectrum data. To perform this verification, the verifier 110may calculate degrees of similarity between the generated values and thecurrently measured spectrum data, a degree of difference therebetween,or a statistical data thereof. If the calculated value is higher than acertain criterion, it may be determined that the spectrum data haspassed the repeatability verification.

The number of spectrum data being described is just an example, and isnot limiting.

In yet another example, the predefined repeatability verificationcriteria may be the combination of a similarity verification and adifference verification. For example, spectrum data may have therepeatability verification results according to the similarityverification and the difference verification. In this case, only if allthe two types of verification results have been passed, the verifier 110may pass the repeatability verification. Alternatively, the verifier 110may pass the repeatability verification even in the case where any oneof the two verification results is passed. Alternatively, the verifier110 put a weight value on any one of the two types of verificationresults, and based on the addition result thereof, the verifier 530 maypass the repeatability verification only when the condition of therepeatability verification is satisfied.

The controller 130 may, based on the verification result, controlwhether the spectroscope 10 will remeasure the spectrum data.

In response to the repeatability verification determination, by theverifier, indicating that the spectrum data has passed the repeatabilityverification, the controller 130 may control an apparatus for analyzingspectrum data (hereinafter, referred to as ‘analysis apparatus’) toanalyze the relevant spectrum data. Meanwhile, in the case where thespectrum data passes the repeatability verification, the controller 130may control the spectroscope to remeasure spectrum data.

Moreover, in response to the repeatability verification determinationindicating that the spectrum data has passed the repeatabilityverification, the controller 130 may control the analysis apparatus toanalyze at least one of a plurality of the measured spectrum data basedon at least one among the following: the number of spectrum data havingpassed the repeatability verification, a rate thereof, and the number oftimes that each spectrum data has failed to pass the repeatabilityverification. However, for example, if the spectrum data has passed therepeatability verification but one of the spectrum data seems muchdifferent from the other spectrum data, the controller 130 may analyzeonly the other spectrum data, excluding the corresponding spectrum data.

Furthermore, based on at least one of the number of spectrum data havingpassed the repeatability verification, a rate thereof, and the number oftimes that each spectrum data has failed to pass the repeatabilityverification, the controller 130 may determine the number ofremeasurement times, and control the spectroscope to remeasure spectrumdata depending on the determined number of remeasurement times. Forexample, if the spectrum data has passed the repeatability verificationbut one of the spectrum data seems much different from the otherspectrum data, the controller 130 may control the spectroscope tomeasure the spectrum data the same number of times as the previouslymeasured one. Meanwhile, if two or more of the spectrum data seem muchdifferent from the other spectrum data, the controller 130 may controlthe spectroscope to measure the spectrum data the greater number oftimes than the previously measured one.

FIGS. 2A and 2B are examples for the description of spectrum dataaccording to an exemplary embodiment.

If a spectroscope repeatedly measures the spectrum data of the same usersample, each of the spectrum data may be measured to be different due tothe following factors: a performance of the spectroscope itself, a stateof the user sample at a time when the spectrum data thereof is measured,external noises, etc.

Referring to FIGS. 1 and 2A, in the case where the spectroscope measuresspectrum data SD1, SD2, and SD3 at three times, the three spectrum dataSD1, SD2, and SD3 may be measured to be similar to each other. In thiscase, a verifier 110 may determine that the three spectrum data meetrepeatability verification criteria, and the controller 130 maydetermine to analyze the three measured spectrum data.

Referring to FIGS. 1 and 2B, in the case where the spectroscope measuresspectrum data SD1, SD2, and SD3 of the same user sample at three times,two of the three spectrum data SD1, SD2, and SD3, i.e., SD1 and SD2, maybe measured to be similar, and one spectrum data, i.e., SD3, may bedifferent. In this case, the verifier 110 may determine that thespectrum data does not meet repeatability verification criteria.

FIG. 3 is a diagram illustrating a method of verifying the repeatabilityof spectrum data by a verifier 110 according to an exemplary embodiment.

Referring to FIG. 3, the verifier 110 may receive spectrum data from aspectroscope. For example, in the case where a spectroscope measuresthree spectrum data SD1, SD2, and SD3 from the same user sample, theverifier 110 may verify the repeatability of the spectrum data, measuredby the spectroscope, based on predefined repeatability verificationcriteria.

Here, the predefined repeatability verification criteria may include asimilarity verification, a difference verification, a statisticalverification, or a combination of two or more of the verificationcriteria The verifier 110 may obtain an operation value that is requiredaccording to the repeatability verification criteria.

If the verifier 110 uses, for example, the similarity verification asthe predefined repeatability verification criteria, the verifier 110 maycalculate degrees of similarity between a plurality of spectrum datathat is measured by the spectroscope, and verify the repeatability basedon the calculated degrees of similarity. That is, the operation valuemay be the degree of similarity Here, a method of calculating the degreeof similarity may be at least one of Pearson correlation, Kendallcorrelation, and Spearman correlation.

For example, in the case where the degree of similarity is calculatedusing Pearson correlation, the verifier 110 may calculate the degree ofsimilarity as shown in Equation 1 below

$\begin{matrix}{r = \frac{\sum_{i = 1}^{n}{\left( {x_{i} - \overset{\_}{x}} \right)\left( {y_{i} - \overset{\_}{y}} \right)}}{\sqrt{\sum_{i = 1}^{n}\left( {x_{i} - \overset{\_}{x}} \right)^{2}}\sqrt{\sum_{i = 1}^{n}\left( {y_{i} - \overset{\_}{y}} \right)^{2}}}} & \left\lbrack {{Equation}\mspace{14mu} 1} \right\rbrack\end{matrix}$

Here, ‘r’ indicates a degree of similarity; ‘x_(i)’ and ‘y_(i)’, twospectrum data for the comparison of the degrees of similarity; and x andy, an average value of the spectrum data.

That is, an operation value A is a degree of similarity between the twospectrum data SD1 and SD2; an operation value B, a degree of similaritybetween the two spectrum data SD2 and SD3; and an operation value C, adegree of similarity between the two spectrum data SD3 and SD1.

Comparing each of the degrees of similarity calculated above to athreshold, the verifier 110 may verify the repeatability of the spectrumdata, measured by the spectroscope, based on the number of the degreesof similarity greater than or equal to the threshold.

A threshold may be, for example, 0.8; and the standard number of degreesof similarity greater than or equal to the threshold may be greater thanor equal to ‘3’. For example, in the case where the operation values 1,2, and 3 are, respectively, ‘0.9’, ‘0.85’, and ‘0.95’, it means thatthey are all greater than or equal to the threshold and meet thestandard number of the degrees of similarity greater than or equal tothe threshold, which thus indicates that they meet repeatabilityverification criteria. In this case, the verifier 110 may determine thatthe three spectrum data SD1, SD2, and SD3 have passed the repeatabilityverification.

In yet another example, in the case where the operation values 1, 2, and3 are, respectively, ‘0.9’, ‘0.6’, and ‘0.5’, the operation values 2 and3 are smaller than the threshold, and the operation value A is greaterthan the threshold. Here, the number of the operation values greaterthan the threshold is one, which means that this case does not satisfythe standard number of the degrees of similarity that are greater thanor equal to the threshold. In this case, the verifier 110 may determinethat the three spectrum data SD1, SD2, and SD3 have not passed therepeatability verification.

However, in the case where it is assumed that the standard number of thedegrees of similarity greater than or equal to the threshold is greaterthan or equal to ‘1’, the verifier 110 may determine that the threespectrum data SD1, SD2, and SD3 have passed the repeatabilityverification. Here, the verifier 110 may detect the causative spectrumdata that makes the operation values 2 and 3 smaller than the threshold.For example, the verifier 110 may detect SD3, which is included incommon when the operation values 2 and 3 are each calculated, as acausative spectrum data that makes the operation values 2 and 3 smallerthan the threshold. In this case, the verifier 110 may determine thatthe spectrum data SD1 and SD2 have passed the repeatabilityverification, excluding SD3.

In another example, if the verifier 110 uses the difference verificationas the predefined repeatability verification criteria, the verifier 110may calculate a degree of difference between a plurality of spectrumdata, which is measured from the spectroscope, and verify therepeatability based on the calculated degree of difference. That is, anoperation value may be a degree of difference. Here, a method ofcalculating the degree of difference may be at least one of Euclideandistance, Manhattan distance, and Hamming distance.

For example, in the case where the degree of difference is calculatedusing Euclidean distance, the verifier 110 may calculate the degree ofdifference as shown in Equation 2 below.d=√{square root over (Σ_(i=1) ^(n)(x _(i) −y _(i))²)}  [Equation 2]

Here, ‘d’ indicates a degree of difference; and ‘x_(i)’ and ‘y_(i)’, twospectrum data for the comparison of the degree of difference

Comparing each of the degrees of difference calculated above to athreshold, the verifier 110 may verify the repeatability of the spectrumdata, measured by the spectroscope, based on the number of the degreesof difference less than or equal to the threshold

A threshold may be, for example, 0.2; and the standard number of degreesof difference less than or equal to the threshold may be greater than orequal to ‘3’ For example, in the case where the operation values 1, 2,and 3 are, respectively, ‘0.1’, ‘0.15’, and ‘0.2’, it means that theyare all less than or equal to the threshold and meet the standard numberof the degrees of difference less than or equal to the threshold, whichthus indicates that they meet repeatability verification criteria, Inthis case, the verifier 110 may determine that the three spectrum dataSD1, SD2, and SD3 have passed the repeatability verification.

In yet another example, in the case where the operation values 1, 2, and3 are, respectively, ‘0.1’, ‘0.25’, and ‘0.3’, the operation values 2and 3 are greater than or equal to the threshold, and the operationvalue A is less than or equal to the threshold. Here, the number of theoperation values less than the threshold is one, which means this casedoes not satisfy the standard number of the degrees of difference lessthan the threshold In this case, the verifier 110 may determine that thethree spectrum data SD1, SD2, and SD3 have not passed the repeatabilityverification.

However, in the case where it is assumed that the standard number of thedegrees of difference less than or equal to the threshold is greaterthan or equal to ‘1’, the verifier 110 may determine that the threespectrum data SD1, SD2, and SD3 have passed the repeatabilityverification. Here, the verifier 110 may detect the causative spectrumdata that makes the operation values 2 and 3 greater than or equal tothe threshold. For example, the verifier 110 may detect SD3, which isincluded, in common when the operation values 2 and 3 are eachcalculated, as a causative spectrum data that makes the operation values2 and 3 greater than or equal to the threshold. In this case, theverifier 110 may determine that the spectrum data SD1 and SD2 havepassed the repeatability verification, excluding SD3.

In yet another example, if the verifier 110 uses the statisticalverification as the predefined repeatability verification criteria, theverifier 110 may calculate statistical data between a plurality ofspectrum data, which is measured from the spectroscope, and verify thebased on the calculated statistical data. That is, an operation valuemay be a statistical data Here, a method of calculating the statisticaldata may be a statistical technique including at least one of a pairedT-test and a paired Z-test.

For example, in the case where the statistical data is calculated usinga paired T-test, the verifier 110 may calculate the statistical data asshown in Equation 3 below

$\begin{matrix}{t = \frac{\overset{\_}{X_{D}}}{S_{D}/\sqrt{n}}} & \left\lbrack {{Equation}\mspace{14mu} 3} \right\rbrack\end{matrix}$

Here, ‘t’ indicates statistical data; ‘X_(D)’, a set of differences oftwo spectrum data (X_(D)={(x₁−y₁), (x₂−y₂), . . . , (x_(n)−y_(n))});X_(D) , an average of X_(D); and S_(D), a variance thereof.

As in the description above regarding the similarity or differenceverification, in the case where the statistical verification is used,the verifier 110 may compare each of the statistical data, calculatedabove, to a threshold, thereby based on the number of the degrees ofsimilarity less than or equal to the threshold, verifying therepeatability of the spectrum data measured by the spectroscope.

In still yet another example, if the verifier 110 uses the combinationof two or more of the similarity verification, the differenceverification, and the statistical verification, the verifier 110 maycalculate degrees of similarity between a plurality of spectrum datameasured by the spectroscope, degrees of difference therebetween, andstatistical data thereof, and verify the repeatability based on thecalculated degrees of similarity, degrees of difference, and statisticaldata. For example, in the case where the spectrum data SD1, SD2, and SD3have the following results of the similarity verification, differenceverification, and statistical data verification, the verifier 110 mayverify the repeatability through a combination of each result.

TABLE 1 Verification Result Similarity Verification Passed DifferenceVerification Not passed Statistical Verification Passed

Under the determination that only when all the similarity verification,the difference verification, and the statistical verification have beenpassed, the spectrum data has passed the repeatability verification, theverifier 110 may determine that the spectrum data above have failed topass the repeatability verification.

In another example, under the determination that only when two or moreof the similarity, difference, and statistical verification have beenpassed, the repeatability verification is passed, the verifier 110 maydetermine that the spectrum data has passed the repeatabilityverification.

In yet another example, the verifier 110 may determine whether therepeatability verification is passed in the repeatability verificationcriteria by putting a weight on the results of the similarity,difference, and statistical verification. For example, the passage ofthe similarity verification leads to the determination of a weight of‘0.5’; the passage of the difference verification, a weight of ‘0.3’;and the passage of the statistical verification, a weight of ‘0.2’. Inthe case where each of the weights is added together thus being greaterthan or equal to ‘0.7’, it may be determined that the repeatabilityverification is passed. In this case, the verifier 110 may add theweights, resulting in ‘0.7’, which means that the repeatabilityverification has been passed.

The operation value, threshold, and weight being used in the exemplaryembodiments above are examples for those skilled in the art preciselyunderstanding and easily implementing the features of the presentapplication, to which the scope of claims thereof is not limited.Moreover, the exemplary embodiments above may be combined and modifiedwithin the scope of claims that are easily derived by those skilled inthe art.

FIG. 4 is a diagram illustrating a controller according to an exemplaryembodiment.

Referring to FIG. 4, the controller 130 includes a remeasurementdeterminer 131, a remeasurement controller 133, and a spectrum dataanalysis controller 135.

If spectrum data fails to pass a repeatability verification, thecontroller 130 may control a spectroscope to remeasure spectrum data.Meanwhile, if the spectrum data has passed the repeatabilityverification, the controller 130 may control an apparatus for analyzingthe spectrum data (hereinafter, referred to as ‘analysis apparatus’) toanalyze the measured spectrum data.

According to the verification result of the verifier 110, theremeasurement determiner 131 may determine whether to remeasure spectrumdata or to analyze the measured spectrum data, based on at least one ofthe following: the number of spectrum data having passed therepeatability verification, a rate thereof, and the number of times thateach spectrum data has failed to pass the repeatability verification.

The remeasurement determiner 131 may, for example, determine whether toremeasure spectrum data based on the number of spectrum data havingpassed the repeatability verification. The verifier 110 verifies therepeatability of the spectrum data based on the similarity verification,thereby resulting in an assumption that there are in total threespectrum data being repeatedly measured. Here, in the case where two ormore spectrum data have passed the repeatability verification, theremeasurement determiner 131 may determine to analyze the spectrum data.Meanwhile, in the case of the spectrum data less than two having passedthe repeatability verification, the determiner 131 may determine toremeasure the spectrum data.

In another example, the remeasurement determiner 131 may determinewhether to remeasure spectrum data based on a rate of the spectrum datahaving passed the repeatability verification. For example, if theverifier 110 verifies the repeatability of the spectrum data based onthe similarity verification. Then, in the case where 70% or more of therepeatedly measured spectrum data has passed the repeatabilityverification, the remeasurement determiner 131 may determine to analyzethe spectrum data. Meanwhile, in the case where 70% or less of therepeatedly measured spectrum data has passed the repeatabilityverification, the remeasurement determiner 131 may determine toremeasure the spectrum data.

In yet another example, the remeasurement determiner 131 may determinewhether to remeasure the spectrum data based on the number of times thateach spectrum data has failed to pass the repeatability verification.The verifier 110 may, for example, verify repeatability of the spectrumdata based on similarity, difference, and statistical verifications. Inthe case where among the repeatedly measured spectrum data, there aretwo or more spectrum data, of which the number of times that thespectrum data has failed to pass the repeatability verification is lessthan twice, the remeasurement determiner 131 may determine to analyzethe spectrum data. Meanwhile, in the case where the number of thespectrum data thereof is less than two, the remeasurement determiner 131may determine to remeasure the spectrum data.

The number of spectrum data, a rate thereof, and the number of timesbeing described is just an example, and is not limiting.

Based on at least one of the number of spectrum data having passed therepeatability verification, a rate thereof, and the number of times thateach spectrum data has failed to pass the repeatability verification,the remeasurement controller 133 may determine the number ofremeasurement times, and then control the spectroscope to remeasurespectrum data depending on the determined number of remeasurement times.

For example, the remeasurement controller 133 may determine the numberof remeasurement times based on the number of the spectrum data havingpassed the repeatability verification. The remeasurement controller 133may, for example, determine to remeasure the spectrum data by increasingthe number of remeasurement times so that the number of the spectrumdata having passed the repeatability verification is inverselyproportional to the total number of spectrum data. For example, in thecase where among a total of five spectrum data, there are four number ofthe spectrum data having passed the repeatability verification, thenumber of remeasurement times may be determined to be five times.Meanwhile, in the case where there are three spectrum data having passedthe repeatability verification among a total of five spectrum data, theremeasurement controller 133 may determine the number of remeasurementtimes to be seven times.

In another example, the remeasurement controller 133 may determine thenumber of remeasurement times based on a rate of the spectrum havingpassed the repeatability verification. The remeasurement controller 133may, for example, determine to remeasure the spectrum data by increasingthe number of remeasurement times in inverse proportion to the rate ofthe spectrum data having passed the repeatability verification. Forexample, in the case where the rate of the spectrum data having passedthe repeatability verification is greater than or equal to 70%, theremeasurement controller 133 may determine the number of measurementtimes to be five times. Meanwhile, in the case where the rate thereofless than 70%, the remeasurement controller 133 may determine the numberof remeasurement times to be seven times.

In yet another example, the remeasurement controller 133 may determinethe number of remeasurement times based on the number of times that eachspectrum data has failed to pass the repeatability verification. Forexample, the remeasurement controller 133 may verify repeatability ofspectrum data based on similarity, difference, and statisticalverifications. In the case where among a total of five spectrum databeing repeatedly measured, there are four spectrum data, of which thenumber of times that the spectrum data has failed to pass therepeatability verification is less than twice, the remeasurementcontroller 133 may determine the number of remeasurement times to befive times. Meanwhile, in the case where there are three spectrum dataamong the total of five spectrum data, the remeasurement controller 133may determine the number of remeasurement times to be seven times.

In still yet another example, the remeasurement controller 133 maydetermine the number of remeasurement times based on a combination ofthe following: the number of spectrum data having passed therepeatability verification, a rate thereof, and the number of times thateach spectrum data has failed to pass the verification.

The number of spectrum data, a rate thereof, and the number of timesbeing described is just an example, and is not limiting.

The remeasurement controller 133 may determine the number ofremeasurement times based on at least one of the number of spectrum datahaving passed the repeatability verification, a rate thereof, and thenumber of times that each spectrum data has failed to pass therepeatability verification, and then control the spectroscope bytransmitting a control signal including the number of remeasurementtimes to the spectroscope so as to remeasure spectrum data depending onthe determined number of remeasurement times.

The spectrum data analysis controller 135 may control the analysisapparatus to analyze at least one of a plurality of measured spectrumdata, based on at least one of the following: the number of spectrumdata having passed the repeatability verification, a rate thereof, andthe number of times that each spectrum data has failed to pass therepeatability verification.

For example, the spectrum data analysis controller 135 may control theanalysis apparatus to analyze at least one of the plurality of themeasured spectrum data based on the number of the spectrum data havingpassed the repeatability verification. For example, in the case wherethe number of the spectrum data having passed the repeatabilityverification is two, the spectrum data analysis controller 135 maycontrol the analysis apparatus to analyze only the two spectrum data.Alternatively, in the case where the number of the spectrum data havingpassed the repeatability verification is two, the spectrum data analysiscontroller 135 may control the analysis apparatus to analyze one of thetwo spectrum data according to a predetermined rule. Alternatively, inthe case where the number of the spectrum data having passed therepeatability verification is two, the spectrum data analysis controller135 may control the analysis apparatus to analyze all the spectrum datathat has failed to pass the verification, as well as the two spectrumdata having passed the verification.

In another example, the spectrum data analysis controller 135 maycontrol the analysis apparatus to analyze at least one of the pluralityof the measured spectrum data based on the rate of the spectrum datahaving passed the repeatability verification. For example, in the casewhere the rate of the spectrum data having passed the repeatabilityverification is greater than or equal to 70%, the spectrum data analysiscontroller 135 may control the analysis apparatus to analyze the entireof the spectrum data. Alternatively, in the case where the rate of thespectrum data having passed the repeatability verification is greaterthan or equal to 70%, the spectrum data analysis controller 135 maycontrol the analysis apparatus to analyze only the spectrum data havingpassed the verification. Alternatively, in the case where the rate ofthe spectrum data having passed the repeatability verification isgreater than or equal to 70%, the spectrum data analysis controller 135may control the analysis apparatus to analyze only one of the spectrumdata having passed the verification, according to a predetermined rule.

In yet another example, the spectrum data analysis controller 135 maycontrol the analysis apparatus to analyze at least one of the pluralityof the measured spectrum data based on the number of times that eachspectrum data has failed to pass the verification. For example, thespectrum data analysis controller 135 may control the analysis apparatusto analyze only the spectrum data, of which the number of times thateach spectrum data has failed to pass the verification is zero. Inanother example, the spectrum data analysis controller 135 may controlthe analysis apparatus to analyze only the spectrum data, of which thenumber of times that each spectrum data has failed to pass theverification is less than or equal to one.

The number of spectrum data, a rate thereof, and the number of timesbeing described is just an example, and is not limiting.

In response to a request for analyzing two or more spectrum data, thespectrum data analysis controller 135 may request the analysis apparatusto analyze each spectrum data. Alternatively, in response to a requestfor analyzing two or more spectrum data, the spectrum data analysiscontroller 135 may request the analysis apparatus to analyze thespectrum data that is generated using at least one of the values ofmean, median, max, and min of each spectrum data.

FIG. 5 is a diagram illustrating an analysis apparatus 500, including aprocessor or a microprocessor, for analyzing spectrum data according toan exemplary embodiment. The analysis apparatus 500 may refer to ahealthcare device, such as smartphones, tablet PCs, laptops,smartwatches, smartbands, and smartglasses, which are capable ofmeasuring physiological parameters including a user's blood pressure,body fat percentage, blood sugar, and triglyceride percentage.

Referring to FIG. 5, the analysis apparatus 500 includes a spectroscopyunit 510, a verifier 530, a calculator 550, and an information provider570, e.g., an output unit or an output transmitter.

The examples of the spectroscopy unit 510 and the verifier 530 in FIG. 5may be, respectively, a spectroscope 10 and a verification apparatus 100for verifying repeatability, which are both illustrated in FIG. 1.

FIG. 6 is a diagram illustrating a spectroscopy unit 510 according to anexemplary embodiment.

Referring to FIGS. 5 and 6, the spectroscopy unit 510 includes a lightsource 511 that irradiates light to a user sample, a detector 513, e.g.,a sensor or sensors, that detect the light reflected from the usersample 600, and a spectrum acquirer 515, e.g., a sensor and/or aprocessor, to acquire spectrum data from the detected light.

The analysis apparatus 500 may refer to a smartband. The smartband maybe worn on a user's wrist, and the user's wrist may refer to the usersample 600. The smartband may include the spectroscopy unit 510, whichis located in the part thereof that is in contact with the user's wrist.In this case, the light source 511 may irradiate light to the user'swrist, and then the detector 513 may detect the reflected light from theskin on the user's wrist.

A spectroscope may be classified according to a spectroscopy. Forexample, the spectroscopy being used by the spectroscope may refer to atleast one of the following spectroscopies: nuclear magnetic resonance(NMR), infrared spectroscopy (IR), Raman spectroscopy, X-rayfluorescence (XRF), gamma spectroscopy, ultraviolet-visible spectroscopy(UV-Vis), near-infrared spectroscopy (NIR), Auger electron Spectroscopy(AES), X-ray photoelectron spectroscopy (XPS), atomic absorptionspectroscopy (AAS), and inductively coupled plasma-atomic emissionspectroscopy (ICP-AES).

The light source 511 may generate a light of a particular wavelengthaccording to a spectroscopy being used. For example, in the case wherethe spectroscope uses the NIR, the light source may generate anear-infrared signal. The light generated through such an operation maybe irradiated to the user sample, and a part of the irradiated light isreflected therefrom and then detected by the detector 513. The detectormay convert the detected light to an electrical signal.

Thus, the light source 511 and the detector 513 may be located in thesame plane of the analysis apparatus 500, and located close to eachother so as to improve the detection performance of the reflected light.

The spectrum acquirer 515 may generate each spectrum data regarding thedetected light. The spectrum acquirer 515 is electrically connected tothe detector 513 so as to receive the electrical signal regarding thedetected light from the detector 513. The spectrum acquirer 515 maygenerate the spectrum data by analyzing an intensity of the detectedlight according to a frequency thereof based on the received electricalsignal

The spectrum acquirer 515 may repeatedly receive an electrical signalregarding the same user sample 600 from the detector 513. For example,the spectrum acquirer 515 may receive the electrical signals three timesregarding the same user sample 600. In this case, the spectrum acquirer515 may generate three spectrum data regarding each detected light fromthe detector 513.

The verifier 530 may verify the repeatability of the spectrum data,acquired by the spectroscopy unit, based on predefined repeatabilityverification criteria. To perform the verification, the verifier 530 maybe electrically connected to the spectrum acquirer 515.

The verifier 530 may receive the spectrum data from the spectrumacquirer 515. The predefined repeatability verification criteria mayinclude a similarity verification, a difference verification, astatistical verification, or a combination of two or more of theverification criteria.

The predefined repeatability verification criteria may be, for example,the similarity verification. In the case where the verifier 530 receivesthe input of three spectrum data from the spectroscope, the verifier 530may calculate degrees of similarity between the three spectrum data.Here, in the case where the resultant similarities between the threespectrum data are greater than or equal to a certain criterion, it maybe determined that all the three spectrum data have passed therepeatability verification. Meanwhile, in the case where similarities ofa part of the three spectrum data are less than a certain criterion, theverifier 530 may determine that the corresponding spectrum data has notpassed the repeatability verification. The number of spectrum data beingdescribed is just an example, and is not limiting.

In another example, the predefined repeatability verification criteriamay be the combination of a similarity verification and a differenceverification. For example, in the case where the verifier 530 receivesthe input of the three spectrum data from the spectroscope, the verifier530 may calculate the similarities between the three spectrum data andthe differences therebetween. Here, the spectrum data may have therepeatability verification results according to the similarityverification and the difference verification. In this case, for example,only if all the two types of verification results have been passed, theverifier 530 may pass the repeatability verification. In anotherexample, the verifier 530 may pass the repeatability verification evenin the case where any one of the two verification results is passed. Inyet another example, the verifier 530 may put a weight value on any oneof the two types of verification results, and based on the additionresult thereof, the verifier 530 may pass the repeatability verificationonly when the condition of the repeatability verification is satisfied.

The verifier 530 may, based on the verification result, control whetherthe spectroscope will remeasure the spectrum data.

The verifier 530 may determine whether to analyze spectrum data, or toremeasure the spectrum data, based on at least one of the following: thenumber of spectrum data having passed the repeatability verification, arate thereof, and the number of times that each spectrum data has failedto pass the repeatability verification.

In one example, the verifier 530 may determine whether to remeasure thespectrum data based on the number of the spectrum data having passed therepeatability verification. For example, in the case where therepeatability of three spectrum data is verified, and all the threespectrum data have passed the repeatability verification, the verifier530 may determine whether to analyze the spectrum data, or otherwise,may determine to remeasure the spectrum data.

The verifier 530 may determine whether to remeasure the spectrum databased on the number of spectrum data having passed the repeatabilityverification. The verifier 530 may verify the repeatability of thespectrum data based on, for example, a similarity verification. In thecase where among a total of three spectrum data being repeatedlymeasured, the two or more spectrum data have passed the repeatabilityverification, the verifier 530 may determine to analyze the spectrumdata. Meanwhile, in the case where the number of the spectrum datahaving passed the repeatability verification is less than two, theverifier 530 may determine to remeasure the spectrum data.

In another example, the verifier 530 may determine whether to remeasurespectrum data based on a rate of the spectrum data having passed therepeatability verification. For example, if the verifier 530 verifiesthe repeatability of the spectrum data based on the similarityverification. Then, in the case where 70% or more of the repeatedlymeasured spectrum data has passed the repeatability verification, theverifier 530 may determine to analyze the spectrum data. Meanwhile, inthe case where 70% or less of the repeatedly measured spectrum data haspassed the repeatability verification, the verifier 530 may determine toremeasure the spectrum data.

In yet another example, the verifier 530 may determine whether toremeasure the spectrum data based on the number of times that eachspectrum data has failed to pass the repeatability verification. Theverifier 530 may, for example, verify repeatability of the spectrum databased on similarity, difference, and statistical verifications. In thecase where among the repeatedly measured spectrum data, there are two ormore spectrum data, of which the number of times that the spectrum datahas failed to pass the repeatability verification is less than twice,the verifier 530 may determine to analyze the spectrum data. Meanwhile,in the case where the number of the spectrum data thereof is less thantwo, the remeasurement determiner 131 may determine to remeasure thespectrum data.

The number of spectrum data, a rate thereof, and the number of timesbeing described is just an example, and is not limiting.

The verifier 530 may control the calculator 550 to analyze at least oneof the plurality of the measured spectrum data based on at least one ofthe following: the number of spectrum data having passed therepeatability verification, a rate thereof, and the number of times thateach spectrum data has failed to pass the repeatability verification.

For example, the verifier 530 may control the analysis apparatus toanalyze at least one of the plurality of the measured spectrum databased on the number of the spectrum data having passed the repeatabilityverification. For example, in the case where the number of the spectrumdata having passed the repeatability verification is two, the verifier530 may control the analysis apparatus to analyze only the two spectrumdata, or to analyze one of the two spectrum data according to apredetermined rule. Alternatively, the verifier 530 may control theanalysis apparatus to analyze all the spectrum data that has failed topass the verification, as well as the two spectrum data having passedthe verification.

In another example, the verifier 530 may control the analysis apparatusto analyze at least one of the plurality of the measured spectrum databased on the rate of the spectrum data having passed the repeatabilityverification. For example, in the case where the rate of the spectrumdata having passed the repeatability verification is greater than orequal to 70%, the verifier 530 may control the analysis apparatus toanalyze the entire of the spectrum data, or to analyze only the spectrumdata having passed the verification. Alternatively, the verifier 530 maycontrol the analysis apparatus to analyze only one of the spectrum datahaving passed the verification, according to a predetermined rule.

In yet another example, the verifier 530 may control the analysisapparatus to analyze at least one of the plurality of the measuredspectrum data based on the number of times that each spectrum data hasfailed to pass the verification. For example, the verifier 530 maycontrol the analysis apparatus to analyze only the spectrum data, ofwhich the number of times that each spectrum data has failed to pass theverification is zero. In another example, the verifier 530 may controlthe analysis apparatus to analyze only the spectrum data, of which thenumber of times that each spectrum data has failed to pass theverification is less than or equal to one.

The number of spectrum data, a rate thereof, and the number of timesbeing described is just an example, and is not limiting.

In response to a request for analyzing two or more spectrum data, theverifier 530 may send a request to the calculator 550 so that theanalysis apparatus analyzes each spectrum data. Alternatively, inresponse to a request for analyzing two or more spectrum data, theverifier 530 may send a request to the calculator 550 so that theanalysis apparatus analyzes the spectrum data that is generated using atleast one of the values of mean, median, max, and min of each spectrumdata.

The calculator 550 may generate user sample analysis information byanalyzing, based on the verification result, at least a part of thespectrum data that is acquired from the spectroscopy unit.

For example, in the case where the verifier 530 makes a request foranalyzing two or more spectrum data, the calculator 550 may generate theuser sample information by analyzing the spectrum data by using thespectrum data, which is calculated using at least one of the values ofmean, median, max, and min of each spectrum data.

In another example, in the case where the verifier 530 makes a requestfor analyzing the two or more spectrum data, the calculator 550 maygenerate the user sample analysis information by using a result value,which is calculated using at least one of the values of mean, median,max, and min.

The user sample information may be, for example, a user's bloodpressure, body fat percentage, blood sugar, cholesterol concentrations,triglyceride percentage, the number of blood cells, enzymeconcentration, hormone concentration, and glomerular filtration rate.

The information provider 570 may provide a user with the generated usersample analysis information.

The information provider 570 is electrically connected to the calculator550, so that the information provider 570 may receive the user sampleanalysis information from the calculator 550 to provide a user with thegenerated user sample analysis information by using at least one ofvisual, auditory, and tactile ways.

The information provider 570 may include, for example, a display toprovide the user sample analysis information to a user as the visualway. In the case where the information provider 570 provides a user'sblood sugar information to the user, the information provider 570 maydisplay characters and numbers together, e.g., “blood sugar: 120 mg/dl”.

The information provider 570 may include, for example, a speaker toprovide the user sample analysis information to a user as the auditoryway. In the case where the information provider 570 provides a user'sblood sugar information to the user, the information provider 570 maygenerate an audio signal, which is then output through the speaker,e.g., “Your blood sugar is 120 mg/dl.”

The information provider 570 may include, for example, a vibratingdevice to provide the user sample analysis information to a user as thetactile way. In the case where the information provider 570 provides auser's blood sugar information to the user, and the provided blood sugarexceeds a value of a set blood sugar, the information provider 570 mayoperate the vibrating device so that a user recognizes the value of theblood sugar is exceeded.

FIG. 7 is a flowchart illustrating a method of verifying repeatabilityaccording to an exemplary embodiment.

Referring to FIG. 7, an apparatus for verifying repeatability(hereinafter, referred to as ‘verification apparatus’) may verify therepeatability based on predefined repeatability verification criteria inoperation 710.

Here, the predefined repeatability verification criteria may include asimilarity verification, a difference verification, a statisticalverification, or a combination of two or more of the verificationcriteria.

The verification apparatus first receives spectrum data from aspectroscope so as to verify the repeatability of the spectrum data, andobtains an operation value of the received spectrum data based on therepeatability verification criteria. For example, the operation valuemay be a degree of similarity, a degree of difference, and statisticaldata depending on the repeatability verification criteria. Afterwards,the verification apparatus may compare the operation value and athreshold, thereby verifying the repeatability of the spectrum data.

When the repeatability is verified, the verification apparatus controlswhether the spectroscope will remeasure the spectrum data based on theverification result in operation 720. Here, the verification apparatusmay determine whether to analyze the spectrum data based on theverification result, or whether to request the spectroscope to remeasurenew spectrum data. Upon determining based on the result that aremeasurement thereof is needed, the verification apparatus requests thespectroscope to remeasure the spectrum data. Otherwise, the verificationapparatus may control to analyze the spectrum data.

FIG. 8 is a detailed flowchart illustrating a method of verifyingrepeatability (hereinafter, referred to as ‘verification apparatus’)according to an exemplary embodiment.

Referring to FIG. 8, the verification apparatus receives spectrum datafrom a spectroscope so as to verify the repeatability of the spectrumdata in operation 711.

Afterwards, the verification apparatus may obtain a necessary operationvalue based on repeatability verification criteria in operation 713 soas to verify the repeatability of the spectrum data that is measured bythe spectroscope based on the predefined repeatability verificationcriteria.

In the case where the verification apparatus, for example, uses asimilarity as the predefined verification criterion, the verificationapparatus may calculate degrees of similarity between a plurality ofspectrum data that is measured by the spectroscope, and verify therepeatability based on the calculated degrees of similarity. In otherwords, the operation value may be the degree of similarity.

In another example, in the case where the verification apparatus uses adifference as the predefined verification criterion, the verificationapparatus may calculate degrees of difference between a plurality ofspectrum data that is measured by the spectroscope, and verify therepeatability based on the calculated degrees of difference. In otherwords, the operation value may be the degree of difference.

In yet another example, in the case where the verification apparatususes statistical verification as the predefined verification criterion,the verification apparatus may calculate statistical data between theplurality of spectrum data that is measured by the spectroscope, andverify the repeatability based on the calculated statistical data. Inother words, the operation value may be the statistical data.

Afterwards, the verification apparatus may compare the operation valueand a threshold, thereby verifying the repeatability of the spectrumdata measured by the spectroscope based on the repeatabilityverification criteria in operation 715.

FIG. 9 is a detailed flowchart illustrating an operation of controllingwhether to remeasure spectrum data according to an exemplary embodiment.

Referring to FIG. 9, in response to the verification result, theverification apparatus determines, as illustrated in operation 721,whether to remeasure spectrum data, or to analyze the measured spectrumdata, based on at least one of the following: the number of spectrumdata having passed the repeatability verification, a rate thereof, andthe number of times that each spectrum data has failed to pass theverification.

The verification apparatus may determine whether to remeasure thespectrum data based on, for example, the number of spectrum data havingpassed the repeatability verification. In the case where there are intotal three spectrum data being repeatedly measured, and the two or morespectrum data have passed the repeatability verification, theverification apparatus may determine to analyze the spectrum data.Meanwhile, in the case where the number of the spectrum data havingpassed the repeatability verification is less than two, the verificationapparatus may determine to remeasure the spectrum data.

In another example, the verification apparatus may determine whether toremeasure the spectrum data based on the rate of the spectrum datahaving passed the repeatability verification. In the case where 70% ormore of the repeatedly measured spectrum data has passed therepeatability verification, the verification apparatus may determine toanalyze the spectrum data. Meanwhile, in the case where 70% or less ofthe repeatedly measured spectrum data has passed the repeatabilityverification, the verification apparatus may determine to remeasure thespectrum data.

In yet another example, the verification apparatus may determine whetherto remeasure the spectrum data based on the number of times that eachspectrum data does not pass the repeatability verification. For example,in the case where among the repeatedly measured spectrum data, there aretwo or more spectrum data, of which the number of times that thespectrum data failed to pass the verification is less than twice, theverification apparatus may determine to analyze the spectrum data.Meanwhile, in the case where the number of the spectrum data havingpassed the repeatability verification is less than two, the verificationapparatus may determine to remeasure the spectrum data.

Afterwards, in the case where the verification apparatus has determinedthat the spectrum data is to be analyzed (NO in operation 723), theverification apparatus requests an apparatus for analyzing spectrum data(hereinafter, referred to as ‘analysis apparatus’) to analyze thespectrum in operation 725. For example, in the case where the spectrumdata has been analyzed, the verification apparatus may depending on theresult, determine which spectrum information of a plurality of themeasured spectrum data to be analyzed, on the basis of at least one ofthe following: the number of spectrum data having passed therepeatability verification, a rate thereof, and the number of times thateach spectrum data has failed to pass the verification. Then, theverification apparatus requests the analysis apparatus to analyze atleast one spectrum data that is determined to be analyzed.

Meanwhile, in the case where the verification apparatus has determinedthat the spectrum data is to be remeasured (YES in operation 723), theverification apparatus requests a spectroscope to remeasure the spectrumdata in operation 727. For example, in the case where analyzing thespectrum data has been performed, the verification apparatus maydepending on the result, determine whether to request the spectroscopeto remeasure the spectrum data on the basis of at least one of thefollowing: the number of spectrum data having passed the repeatabilityverification, a rate thereof, and the number of times that each spectrumdata has failed to pass the verification. Then, the verificationapparatus determines how many spectrum data the verification apparatusrequests to the spectroscope, and depending on the determined numberthereof, requests the spectroscope to remeasure the spectrum data.

The methods and/or operations described above may be recorded, stored,or fixed in one or more non-transitory computer-readable storage mediathat includes program instructions to be implemented by a computer tocause a processor to execute or perform the program instructions. Themedia may also include, alone or in combination with the programinstructions, data files, data structures, and the like. Examples ofcomputer-readable storage media include magnetic media, such as harddisks, floppy disks, and magnetic tape; optical media such as CD ROMdisks and DVDs; magneto-optical media, such as optical disks, andhardware devices that are specially configured to store and performprogram instructions, such as read-only memory (ROM), random accessmemory (RAM), flash memory, and the like. Examples of programinstructions include machine code, such as produced by a compiler, andfiles containing higher level code that may be executed by the computerusing an interpreter. The described hardware devices may be configuredto act as one or more software modules in order to perform theoperations and methods described above, or vice versa In addition, acomputer-readable storage medium may be distributed among computersystems connected through a network and computer-readable codes orprogram instructions may be stored and executed in a decentralizedmanner.

The foregoing exemplary embodiments and advantages are merely exemplaryand are not to be construed as limiting. The present teaching can bereadily applied to other types of apparatuses. Also, the description ofthe exemplary embodiments is intended to be illustrative, and not tolimit the scope of the claims, and many alternatives, modifications, andvariations will be apparent to those skilled in the art

What is claimed is:
 1. A method of verifying repeatability of aspectroscope, the method comprising: performing a repeatabilityverification of a set of spectrum data of a user sample using at leasttwo sets of spectrum data of the user sample, among a plurality ofspectrum data measured by the spectroscope at different points in time,by irradiating light to the user sample and detecting the lightreflected from the user sample, based on a repeatability verificationcriteria; and controlling the spectroscope whether or not to remeasurethe set of spectrum data, based on verification result of therepeatability verification, wherein the set of spectrum data and the atleast two other sets of spectrum data that are measured by thespectroscope are arranged into at least three different pairs comprisinga different combination of sets of spectrum data, respectively, amongthe set of spectrum data and the at least two other sets of spectrumdata, and the performing the repeatability verification furthercomprises comparing the at least three different pairs to each other andapplying the repeatability verification criteria to a result of thecomparing, respectively.
 2. The method of claim 1, wherein therepeatability verification criteria comprise at least one from among asimilarity verification, a difference verification, and a statisticalverification.
 3. The method of claim 2, wherein the at least two othersets of spectrum data are measured by the spectroscope prior tomeasuring the set of spectrum data, and the performing the repeatabilityverification further comprises: performing the repeatabilityverification of the set of spectrum data based on the repeatabilityverification criteria by using at least one from among mean values andmedian values of the at least two other sets of spectrum data.
 4. Themethod of claim 2, wherein the repeatability verification criteriacomprises the similarity verification, and the method further comprises:calculating a degree of similarity between the set of spectrum data andthe at least two other sets of spectrum data, respectively, by using atleast one from among a Pearson correlation, a Kendall correlation, and aSpearman correlation; and performing the repeatability verification ofthe set of spectrum data based on the degree of similarity.
 5. Themethod of claim 2, wherein the repeatability verification criteriacomprises the difference verification, and the method further comprises:calculating a degree of difference between the set of spectrum data andthe at least two other sets of spectrum data, by using at least one fromamong an Euclidean distance, a Manhattan distance, and a Hammingdistance; and performing the repeatability verification of the set ofspectrum data based on the degree of difference.
 6. The method of claim2, wherein the repeatability verification criteria comprises thestatistical verification, and the method further comprises: calculatingstatistical data of the set of spectrum data and the at least two othersets of spectrum data, by using at least one from among a paired T-testand a paired Z-test, and performing the repeatability verification ofthe set of spectrum data based on the statistical data.
 7. The method ofclaim 1, wherein the controlling the spectroscope further comprises:performing the repeatability verification of the set of spectrum dataand the at least two other sets of spectrum data based on therepeatability verification criteria, based on the set of spectrum dataand the at least two other sets of spectrum data having failed to passthe repeatability verification, controlling the spectroscope toremeasure the set of spectrum data and the at least two other sets ofspectrum data; and based on the set of spectrum data and the at leasttwo other sets of spectrum data having passed the repeatabilityverification, controlling an analysis apparatus to analyze the set ofspectrum data and the at least two other sets of spectrum data.
 8. Themethod of claim 7, wherein the controlling the spectroscope furthercomprises: based on at least one from among a number of the set ofspectrum data and the at least two other sets of spectrum data havingpassed the repeatability verification, a rate thereof, and a number oftimes that the set of spectrum data and each of the at least two othersets of spectrum data have failed to pass the repeatabilityverification, controlling the spectroscope by determining a number ofremeasurement times to remeasure the set of spectrum data and the atleast two other sets of spectrum data, or controlling the analysisapparatus by determining which of the set of spectrum data and the atleast two other sets of spectrum data is to be analyzed.
 9. The methodof claim 1, wherein the performing the repeatability verificationfurther comprises: applying the repeatability verification criteria toeach of the at least three different pairs, and determining whether theset of spectrum data and each of the at least two other sets of spectrumdata passed the repeatability verification based on the verificationresult generated for each of the at least three different pairs,respectively.
 10. A non-transitory computer-readable storage mediumstoring at least one instruction which, when executed by a processor,causes the processor to perform the method of claim 1.